CN110313186B

CN110313186B - Acoustic device, acoustic receiver, and integrated circuit

Info

Publication number: CN110313186B
Application number: CN201880012445.8A
Authority: CN
Inventors: C·金; A·昂鲁; D·瓦恩
Original assignee: Knowles Electronics LLC
Current assignee: Knowles Electronics LLC
Priority date: 2017-01-05
Filing date: 2018-01-05
Publication date: 2021-07-06
Anticipated expiration: 2038-01-05
Also published as: US20190327563A1; CN110313186A; US11057718B2; WO2018129242A1; DE112018000317T5

Abstract

The present disclosure provides an acoustic apparatus, an acoustic receiver, and an integrated circuit. Acoustic devices and methods generate an acoustic signal in response to an electrical input signal applied to an acoustic receiver. An electroacoustic transducer is used to convert an acoustic signal into an electrical output signal proportional to the acoustic pressure of the acoustic signal. In some embodiments, the apparatus and methods determine whether there is a change in the acoustic signal indicative of a change in an acoustic load coupled to the receiver by comparing the electrical output signal to reference information. In one example, the change in acoustic loading may be attributable to cerumen accumulation in the output of the acoustic receiver or in an acoustic passage in the ear canal of the user or to seal leakage.

Description

Acoustic device, acoustic receiver, and integrated circuit

RELATED APPLICATIONS

This application relates to U.S. provisional patent application serial No.62/409,341 entitled "article-Based absorbent vehicle Having Improved Output and Method," filed 2016, month 10, 17, the entire contents of which are incorporated herein by reference.

Technical Field

The present disclosure relates generally to acoustic devices, and more particularly, to acoustic load variation diagnostics in acoustic devices, circuits thereof, and corresponding methods.

Background

Acoustic devices are generally known which comprise a balanced armature receiver (receiver) which converts an electrical input signal into an acoustic output signal characterized by a varying Sound Pressure Level (SPL). Such a device may be implemented as a hearing aid, an earphone or an earplug worn by the user. The receiver typically includes a motor having a coil to which an electrical excitation signal is applied. The coil is disposed around a portion of an armature (also referred to as a reed) with the movable portion of the armature disposed equally between the magnets, which are typically held by a yoke. Application of an excitation signal or input signal to the receiver coil modulates the magnetic field, causing reed deflection between the magnets. The deflected spring is connected (link) to a movable part of the diaphragm, called a diaphragm (paddle), arranged in a partially closed receiver housing, wherein the movement of the diaphragm forces air through a sound outlet or port of the housing. The performance of these acoustic devices may be adversely affected by sub-optimal coupling or acoustic output signal blockage and other conditions that tend to alter the acoustic load coupled to the device.

The objects, features and advantages of the present disclosure will become more apparent to those of ordinary skill in the art when the following detailed description is considered with reference to the accompanying drawings.

Disclosure of Invention

The present disclosure provides an acoustic device, including: an armature-based acoustic receiver comprising a housing having a diaphragm coupled to the armature, the diaphragm defining a front volume and a back volume, the front volume coupled to an output of the housing; at least one electro-acoustic transducer located in at least one of the front volume, the back volume, and the output of the receiver; and a circuit operable to determine whether there is a change in the acoustic signal of the receiver based on the pressure sensed by the at least one electro-acoustic transducer, wherein the change in the acoustic signal is indicative of a change in an acoustic load coupled to the receiver, wherein the circuit is operable to determine whether there is a change in the acoustic signal by comparing data representing a measured transfer metric of the receiver, which is a ratio of an acoustic output signal of the receiver to an electrical input signal of the receiver, to data representing an expected transfer metric of the receiver, which is a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference test load.

The present disclosure provides an armature-based acoustic receiver, comprising: a housing having a diaphragm coupled to an armature, the diaphragm defining a front volume and a back volume, the front volume coupled to an output port of the housing; and at least one electroacoustic transducer positioned to sense pressure in at least one of the front volume and the back volume to determine whether there is a change in the acoustic signal of the receiver based on the sensed pressure, wherein the change in the acoustic signal is indicative of a change in an acoustic load coupled to the receiver, wherein the data representing the measured delivery metric of the headphones is compared with the data representing the expected delivery metric of the headphones to determine whether there is a change in the acoustic signal, wherein the measured transfer metric is a ratio of an acoustic output signal of the receiver to an electrical input signal of the receiver, and the expected transfer metric is a ratio of a reference acoustic output signal of the earpiece to a reference electrical input signal of the earpiece for a reference test load.

The present disclosure also provides an integrated circuit, comprising: circuitry operable to apply an electrical input signal at an output of the integrated circuit for an armature-based acoustic receiver; circuitry operable to determine whether there is a change in the acoustic signal of the receiver by comparing a measured transfer metric to an expected transfer metric, the measured transfer metric being a ratio of an acoustic output signal of the receiver to the electrical input signal, and the expected transfer metric being a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference test load.

Drawings

Fig. 1 is a block diagram of a system for generating a predistorted excitation signal for input to an armature-based receiver.

Fig. 2 is a graph of Total Harmonic Distortion (THD) versus SPL for different magnetizations and for different types of input signals or excitation signals without predistortion.

Fig. 3A-3D are comparative illustrative diagrams of receiver output in response to an input signal with and without predistortion.

Fig. 4 is a graph of THD versus SPL for receivers driven by different types of amplifiers, with and without predistortion.

Fig. 5 is a graph of THD versus SPL for receivers driven by different types of amplifiers (including over-magnetized receivers), with and without pre-distortion.

Fig. 6 illustrates the frequency response of a receiver driven by a different type of amplifier.

Fig. 7 is a graph of a calculable nonlinear function having an inverse sigmoid form.

FIG. 8 is a test system for determining parameters of a non-linear function.

Fig. 9 is a schematic block diagram of an integrated circuit for use in combination with a microphone.

Fig. 10 is a schematic block diagram of a receiver.

Fig. 11A and 11B are graphical representations of a computable model of an armature-based receiver.

Fig. 12 is a graph (plot) of relative permeability versus flux density.

Fig. 13 illustrates a system integrated with an armature-based receiver.

Fig. 14 is a block diagram illustrating an example of a system employing acoustic receivers with acoustic load change determination.

Fig. 15 is a flow chart illustrating one example of a method in an acoustic receiver.

Fig. 16 illustrates an example of a method in an acoustic receiver.

Fig. 17 is a graph illustrating example reference information in the form of front cavity frequency response information and a curve indicating a change in acoustic loading from the perspective of the front cavity in an acoustic receiver.

Fig. 18 is a graph illustrating example reference information in the form of back cavity frequency response information and a curve indicating a change in acoustic load from the perspective of the back cavity in an acoustic receiver.

Fig. 19 is a graph illustrating example reference information in the form of output port frequency response information and a curve indicating a change in acoustic load from the perspective of an output port in an acoustic receiver.

FIG. 20 illustrates an example of a user interface.

FIG. 21 illustrates an example of a user interface.

Fig. 22 illustrates an example of sensor positions in an acoustic receiver.

Fig. 23 illustrates an example of sensor positions in an acoustic receiver.

Fig. 24 illustrates an example of sensor positions in an acoustic receiver.

Fig. 25 illustrates an example of sensor positions in an acoustic receiver.

Fig. 26 illustrates an example of sensor positions in an acoustic receiver.

Fig. 27 illustrates an example of sensor positions in an acoustic receiver.

Fig. 28 illustrates an example of a microphone location in an acoustic receiver, where a microphone or circuit element (circuit board, flex circuit, substrate, etc.) attached to the microphone forms part of the receiver housing and defines part of the front volume.

Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity. It will further be appreciated that certain actions or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required unless a particular order is specifically indicated. It will also be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein.

Detailed Description

In general, an acoustic apparatus and method for generating an acoustic output signal in response to an electrical input signal are disclosed. The conversion of the electrical input signal may be performed by acoustic receivers (also referred to herein as "receivers"). In one embodiment, the receiver is implemented as an armature-based receiver comprising an armature connected to a diaphragm, the diaphragm dividing a receiver housing into a front volume and a back volume, wherein the front volume is coupled to an output port of the housing by an acoustic channel. In some embodiments, the acoustic channel includes a nozzle on which the output port is disposed. In other embodiments, the acoustic channel comprises a chamber (also referred to as a doghouse structure) located between the front volume of the receiver and the output port. In other embodiments, the receiver is implemented as a dynamic speaker that includes a diaphragm that divides the receiver housing into a front volume and a back volume. The acoustic device may be implemented as a receiver or a receiver integrated with some other device such as a hearing aid, an earphone, an ear plug or an earpiece or as some other device that generates an acoustic output signal in response to an electrical input signal and is intended for use near the ear of a user.

According to one aspect of the present disclosure, an acoustic output signal of a receiver is converted into an electrical output signal related to a sound pressure of the acoustic signal using one or more electro-acoustic transducers (e.g., microphones) located in, on, or near the acoustic device. In one embodiment, the receiver apparatus includes at least one microphone positioned to detect acoustic pressure in at least one of a front volume, a back volume, or an output channel of the receiver. As described herein, positioning a microphone to sense sound pressure in different areas of a receiver may have different advantages. In some implementations, the sound pressures detected at multiple locations of the receiver housing are also used to determine load changes.

The change in the acoustic output signal is used to determine a change in an acoustic load coupled to the acoustic device. In one embodiment, a notification of a load change is provided or made available to a user or service technician. In another embodiment, the performance of the acoustic device may be automatically adjusted to compensate for changes in acoustic loading. In other embodiments, both notification and compensation are provided. These and other aspects of the disclosure are discussed further herein.

The acoustic load can be generally characterized as the size, shape and leakage associated with the volume of air in which the acoustic pressure of the receiver is generated. For example, a receiver disposed in the earpiece includes an output port that is coupled to a sound port of the earpiece, typically through a sound tube. In use, the earpiece may be coupled to the user's ear with more or less leakage therein. Thus, in this example, the acoustic channel of the earpiece, the ear canal of the user and the leakage coupled therebetween, and other factors contribute to the acoustic loading. Typically, environmental factors such as temperature, humidity and pressure also affect the acoustic load.

In one example, the change in acoustic loading may be due to a blockage (obstruction) of the acoustic output signal of the acoustic device. Such blockage may be caused by accumulation of foreign matter in certain parts of the acoustic device. Foreign matter includes moisture, earwax (also known as cerumen), or other debris that tends to penetrate into the acoustic device, as well as combinations thereof. For example, the blockage may occur in a sound port of an earplug or earpiece of the acoustic device, or in a tube (tube) interconnecting the sound port to an output port of the earpiece. In some acoustic devices, foreign objects may migrate through the structure towards and accumulate in portions of the receiver. The occlusion diagnosis may be performed whether or not the acoustic device is in use. Thus, for occlusion diagnosis, at least one of the sound port of the acoustic device, or any sound tube interconnecting the sound port and the output port of the receiver, or any occlusion of the output port of the receiver may affect the acoustic load.

In another example, the change in acoustic loading may be attributable to a change in acoustic coupling between the hearing device and the user's ear. Such coupling changes may be caused by seal leakage or may be caused by an over-tightened seal associated with the coupling. More generally, the acoustic loading may change for reasons other than the blockage or coupling problems discussed in the above examples. Regardless of the cause, the load change is diagnosed by sensing a change in the acoustic output, as discussed further herein. Diagnosis of coupling problems requires that the acoustic device be coupled to a load (e.g., positioned on a user). For purposes of coupling detection, at least the coupling characteristics (e.g., seal or leakage) between the acoustic device and the user or other equipment to which the acoustic device is acoustically coupled affects the acoustic load.

Typically, the change in acoustic load can be determined by comparing the acoustic output signal with reference information. To this end, the circuit is operable to determine whether there is a change in the acoustic signal of the receiver by comparing an electrical output signal representative of the (presented) acoustic output signal with reference information, wherein the electrical output signal is generated by a microphone positioned to sense the acoustic output of the acoustic device. The reference information is stored in a memory of the circuit. The circuit may also determine the extent or degree of change in the acoustic loading. In some embodiments, the circuit also controls the performance of the receiver by applying equalization to the electrical input signal to compensate for changes in the acoustic loading. The circuit may be implemented by a processor executing an acoustic load change determination algorithm or by an equivalent hardware circuit or a combination thereof. In embodiments where predistortion is also applied, the signal representing the desired acoustic output is equalized prior to the predistortion process.

In one embodiment, the comparison is performed by a circuit integrated with the receiver (e.g. provided in or on the receiver) or by a circuit integrated with another part of the acoustic apparatus with which the receiver is integrated or used in combination. For example, another part of the acoustic device may be a behind-the-ear unit of the hearing device or an in-the-ear earpiece, an earplug, an earphone housing part or some other structure integrated with a receiver. Alternatively, the comparison may be performed by circuitry located remotely from the acoustic device, for example, in a cloud server (web server), mobile device, hearing device testing station, or at a service facility, as well as other remote devices or locations. Remote processing requires that information from the acoustic device (e.g., acoustic output signals or electrical output signals representative thereof) be provided to a remote device or location for processing as discussed herein.

In one embodiment, the reference information is the maximum sound pressure that can be generated at one or more reference frequencies in the front volume of the receiver without the output of the receiver being blocked. In one embodiment, the one or more frequencies are below the resonant frequency of the receiver. The resonant frequency may be a primary mechanical resonant frequency or an acoustic resonant frequency. According to this embodiment, an occlusion may be detected when the acoustic output measured at one or more reference frequencies in the front volume of the receiver is larger than defined reference information. The method is mainly suitable for detecting obstruction and cannot provide a measurement result of the degree of obstruction. The maximum sound pressure as a function of frequency that can be generated in the front volume of the receiver can be calculated or measured at the time of manufacture or created during a post-manufacture calibration procedure.

In other embodiments, the reference information is an expected transfer function comprising a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver. The desired transfer function may be a function of one or more frequencies. In one approach, the expected transfer function is based on the acoustic output as follows: an acoustic output measured over a specified frequency range in response to an electrical input signal having a fixed amplitude. The expected transfer function may be calculated or measured at the time of manufacture or created during a post-manufacture calibration process.

Typically, the expected transfer function is determined for a specified load condition. For example, the expected transfer function may be determined for an unobstructed, non-coupled acoustic device. The different expected transfer functions may be determined for the best coupled acoustic device that is not blocked, for example, by a service technician or a user invoking an initialization algorithm executed by the circuit when the acoustic device is properly coupled (e.g., the device is installed on the user). A coupling sensor on the acoustic device may indicate whether the device is coupled and invoke the appropriate intended transfer function depending on whether diagnostics are performed while the device is coupled.

The expected transfer function (also referred to as sensitivity) of the receiver is substantially linear over the known operating range of the receiver (e.g., in response to a relatively low to medium amplitude electrical input signal). As described in U.S. application No.62/409,341 entitled "array-Based Acoustic Receiver Having Improved Output and Method," filed on 17.10.2016, the application of predistortion to an input signal will increase the linear operating range of the Receiver. However, if the expected delivery is modeled to accommodate the non-linear operation of the receiver, then the change in acoustic loading can be determined for the non-linear operation of the receiver. In any case, if the receiver is operating in its linear range (i.e. the electrical input signal is not large enough to cause non-linear operation of the receiver), the change in load can be determined by comparing the expected transfer function with the measured transfer function.

In these embodiments, the circuit is operable to determine whether there is a change in the acoustic signal by comparing data representing a measured transfer function of the receiver with data representing an appropriate expected transfer function of the receiver. The measured transfer function is the ratio of the acoustic output signal of the receiver to the electrical input signal of the receiver. The measured transfer function is a measure of the transfer function at some time after manufacture. The measured transfer function may be the same as or different from the expected transfer function depending on the acoustic loading conditions. The method is suitable for detecting any load change and allows the degree of change to be determined.

In general, the comparison of the transfer functions may be performed at one or more frequencies. In one implementation, the transfer functions are compared at a single frequency, for example, at a mechanical resonance or an acoustic resonance of the receiver. The difference in amplitude of the transfer function at a particular frequency is indicative of a load change. In some embodiments, the circuit is operable to compare the measured transfer function to an expected transfer function for a range of frequencies between about 1 octave below the resonant frequency of the receiver (octave) and about 1 octave above the resonant frequency of the receiver. In one implementation, the resonant frequency is the main mechanical resonant frequency of the receiver. In another implementation, the resonant frequency is an acoustic resonant frequency of the receiver. In general, the acoustic resonance frequency may be higher or lower than the main mechanical resonance frequency of the receiver. The difference in amplitude of the transfer function at a plurality of frequencies may represent a measure of the slope, which also represents the load change. The difference in amplitude of the transfer function at a plurality of frequencies can be used to locate a maximum or minimum or change in maximum or minimum, a change in corner frequency, any one or more of which can be indicative of a change in acoustic loading.

In some embodiments, the circuit is operable to provide a diagnostic electrical input signal to the receiver to diagnose changes in the acoustic loading. As discussed herein, the acoustic output signal may be represented by an electrical output signal generated by a microphone positioned to detect an acoustic pressure associated with the acoustic output of the receiver. As discussed herein, the acoustic output signal may be represented by an electrical output signal generated by a microphone positioned to detect an acoustic pressure associated with the acoustic output of the receiver. The circuit generates a diagnostic signal. The diagnostic signal may be a single tone with known parameters (e.g., amplitude, frequency, and phase), or a stepped frequency signal with known parameters or a swept frequency signal with known parameters, as well as other signals with known parameters. Other diagnostic signals may also be used, including inter alia chirp (chirp), pink noise, white noise, etc. If a coherence check is performed, a less well defined signal may be used. This type of testing may be done at the time of use of the device, and may be performed at the time of use of the device.

The diagnostic signal may be audible or inaudible. The user is typically unable to perceive the inaudible signal because the frequency is outside the audible range, or because the amplitude or level of the signal in the audible frequency range is below a hearing threshold, or because the signal in the audible frequency range is masked by other sounds that are occurring simultaneously. An input signal with sub-audible frequencies can be optimally detected by an electroacoustic transducer located in the front volume of the receiver. The use of inaudible signals for load change diagnosis purposes will not interrupt the listening enjoyment of the user when the acoustic device is in use. In an embodiment where the measured transfer function is compared to a reference transfer function, the measured transfer function is the ratio of the acoustic output signal to the diagnostic signal.

In other embodiments, the circuit uses a signal from an external source to determine a change in the acoustic load. The electrical input signal obtained from the external source may originate from a microphone in the hearing aid, from an audio playback device or from some other device. In some embodiments, the circuitry conditions a signal obtained from an external source prior to applying the signal to the receiver. For example, a signal obtained from a microphone in a hearing aid device may be subjected to filtering, impedance matching, and amplification before being applied to a receiver. Other external signals may require other processing. Alternatively, the circuit may be used only as a channel for passing signals directly from an external source to the receiver. In embodiments where the measured transfer function is compared to a reference transfer function, the circuit must determine a parameter of the signal from the external source in order to perform the comparison. Such measurements are typically performed at a particular frequency or range of frequencies.

In some embodiments, the electroacoustic transducer is arranged on a substrate, which forms part of the front or back volume or output channel of the receiver, depending on where it is desired to detect the sound pressure. In embodiments where the electroacoustic transducer is positioned to sense acoustic pressure in the back volume or the front volume of the receiver, the electroacoustic transducer substrate forms part of the back volume or the front volume, respectively. In embodiments where the electroacoustic transducer is positioned to sense acoustic pressure in the output channel of the receiver, the electroacoustic transducer substrate forms part of the output channel. As suggested herein, some embodiments may include multiple microphones, and thus the microphone substrate may constitute more than one volume or channel of the receiver.

In some embodiments, an armature-based acoustic receiver includes a housing having a diaphragm defining a front volume, a back volume, and an output port coupled to the front volume. The receiver includes at least one electro-acoustic transducer positioned to sense acoustic pressure in at least one of the front volume and the back volume.

In some embodiments, a circuit implemented as one or more integrated circuits for use in combination with armature-based acoustic receivers is operable to apply an electrical input signal at an output of the integrated circuit. The circuit is further operable to determine whether there is a change in the acoustic signal of the receiver by comparing data representing the acoustic output of the receiver with reference data of the receiver. In one embodiment, the measured transfer metric is compared to data representing an expected transfer function. The measured transfer metric is a ratio of an acoustic output signal of the receiver to an electrical input signal, and the expected transfer function is a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference load.

In some embodiments, the integrated circuit is operable to determine whether there is a change in the acoustic signal by comparing data representing a measured transfer function of the receiver to data representing an expected transfer function of the receiver, wherein the measured transfer function is a ratio of an acoustic output signal of the receiver to an electrical input signal of the receiver and the expected transfer function is a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference test load.

In some embodiments, the integrated circuit is operable to compare the measured transfer function to an expected transfer function for a frequency range between about 1 octave below the receiver resonant frequency and about 1 octave above the receiver resonant frequency.

In some implementations, the integrated circuit is operable to provide a notification when there is a change in the acoustic signal indicative of a change in the acoustic load.

In some embodiments, the circuit determines that a change in the acoustic signal is indicative of a blockage of the output, wherein the expected transfer function is a ratio of a reference acoustic output signal to a reference electrical input signal for a reference test load representing an unblocked receiver. In some embodiments, the integrated circuit determines that a change in the acoustic signal is indicative of a change in the acoustic leakage, wherein the expected transfer function is a ratio of a reference acoustic output signal to a reference electrical input signal for a reference test load comprising a reference leakage.

Armature-based receivers, on the other hand, typically have nonlinear transfer characteristics that depend on various physical and operational characteristics of the transducer. These characteristics include, for example, changing the permeability of the armature due to changes in magnetic flux, etc. The output SPL of the receiver is typically dependent on the amplitude and frequency of the input signal. Receiver non-linearity tends to limit the undistorted output SPL because higher SPLs tend to exacerbate distortion. The maximum output SPL is typically specified for a particular distortion level. As a result, the acoustic output of the receiver may not be an accurate reproduction of the desired acoustic output signal.

The present disclosure relates to improving the performance of armature-based receivers by driving the receiver with a pre-distorted electrical excitation signal. Fig. 1 is a block diagram of a feed-forward system 100 that generates a pre-distorted electrical excitation signal using a computable nonlinear function that represents the behavior of a receiver. When applied to the input of an armature-based receiver, the predistorted electrical excitation signal improves the performance of the receiver at least in part by compensating for the non-linearity of the receiver (including the non-linearity of the magnetic permeability attributable to changes in the armature). This improved performance may result in increased SPL for a given distortion level or increased linearity for a given SPL. These and other aspects and benefits are discussed further below.

Armature-based receivers refer to a class of acoustic transducers having an armature (also referred to as a reed) with a movable portion that deflects relative to one or more magnets in response to application of an excitation signal to a coil of the receiver. Such a receiver may be balanced or unbalanced. With the armature in a steady-state (fixed or stationary) position (i.e., no excitation signal is applied to the coil), an armature-based receiver is ideally balanced when there is no or at least negligible magnetic flux in the armature or no or at least negligible magnetic flux through the armature. When there is magnetic flux in or through the fixed armature in the nominal rest position of the receiver, the receiver is unbalanced. Armature-based receivers with only one magnet are inherently unbalanced. In general, an unbalanced receiver will have a reduced output SPL for a given distortion level compared to a balanced receiver. Such an imbalance may be detected by measuring the second harmonic of the distortion of the output signal that is produced in response to a high amplitude input signal or drive signal. Armature-based receivers may be unbalanced due to deviations from manufacturing tolerances or for some other reason. Also, a balanced armature-based receiver may become unbalanced when changing the rest position of the reed between the magnets. This repositioning of the rest position of the reed may occur due to the influence of the receiver being dropped or some other impact being given to the receiver.

One source of non-linearity in armature-based receivers may be due to changing the permeability of the soft magnetic components of the receiver in response to applying an excitation signal to the receiver coil. Soft magnetic components include, but are not limited to, the armature, yoke or other soft magnetic portion of the receiver. Nickel-iron (Ni-Fe) is a soft magnetic component commonly used in armature-based receivers, but other soft magnetic materials may also be used. The relationship between the external magnetization field H caused by the current in the receiver coil and the magnetic flux density B in the armature is non-linear, especially when driven by an excitation signal having a relatively high amplitude. At some point, when the magnetic field H is strong enough, the magnetic field H cannot further increase the magnetization of the armature, and when the permeability of the material is equal to 1, the armature is said to be fully saturated. In some armature-based receivers, this non-linear relationship between the magnetic field H and the magnetic flux density B is a major source of non-linearity, particularly at high output SPL. However, armature-based receivers exhibit non-linear behavior even when the receiver is operating within a relatively linear portion of the magnetization curve.

Another source of non-linearity in armature-based receivers can be attributed to the force/deflection characteristics of the reed and diaphragm. Ideally, for small displacements, there is a linear relationship between force and deflection as specified by hooke's law. In fact, this relationship is non-linear in many receivers. The air flow in armature based receivers may also be a source of non-linearity, for example, to compensate for variations in atmospheric pressure, small vents are typically provided in the diaphragm membrane to equalize the air pressure in the front and rear chambers of the receiver. However, air flowing through the vent during operation encounters varying resistance to the flow, which results in distortion. There may be other sources of distortion associated with airflow in or through other parts of the receiver or load, including airflow in or through the acoustic output port, any tubing connected to the output port, the load (e.g., the human ear), the load coupling portion, and other components of the receiver. The nonlinear transfer characteristics of other acoustic transducers may arise from other sources specific to the structure of such transducers.

During the manufacture of armature-based receivers, one or more permanent magnets are magnetized by exposure to a strong external polarizing magnetic field. The magnitude of the residual magnetic field induced in the magnet is a major factor in the sensitivity of the receiver. Increasing this residual magnetic field (or magnetization) of the magnet generally increases the sensitivity or efficiency of the receiver, but also increases distortion. An over-magnetized receiver has a reduced output SPL for a given distortion level compared to a receiver that is not over-magnetized. This reduced output SPL tends to increase with increasing magnetization level. Thus, for most use cases, the magnetization level of the receiver needs to be traded off between sensitivity and distortion.

Some armature-based receivers, particularly the magnets or other permanently magnetized portions thereof, are overcharged or over-magnetized, or magnetized to a level higher than best practices generally specified. When the magnetic force is stronger than the mechanical restoring force of the movable part of the armature (i.e. the restoring force of the reed, but not the restoring force of the other parts of the receiver like the diaphragm), the receiver is strongly over-magnetized. In a strongly over-magnetized receiver, the reed will tend to stick to one magnet or another if it deviates from its equilibrium position without loading other components (e.g., the diaphragm). The over-magnetization may be intentional or may result from a deviation from or lack of manufacturing tolerances when charging or magnetizing the magnet or other permanently magnetized portion of the receiver.

Fig. 2 is a graph of Total Harmonic Distortion (THD) versus output SPL for different types of drive signals and for different levels of magnetic charge in an armature-based receiver driven by an electrical excitation signal without predistortion. While 400Hz data is shown, other frequencies or ranges may alternatively be used. Curve 302 represents the THD versus SPL for a receiver that is not over-magnetized, in the case where the receiver coil is driven by a current signal having a frequency of 400 Hz. Curve 304 represents the THD versus SPL for a receiver that is not over-magnetized, in the case where the coil is driven by a voltage signal having a frequency of 400 Hz. Curve 306 represents the THD versus SPL for a receiver in the case where the coil is driven by a current signal having a frequency of 400Hz and the armature is over-magnetized such that the receiver sensitivity (in pascals/volt) increases by 1.5 decibels. Fig. 2 illustrates that for a given distortion level (e.g., five percent (5%)), the output SPL of an over-magnetized receiver is less than the SPL of a receiver that is not over-magnetized. Fig. 2 also illustrates that without predistortion, a current-driven receiver has a lower SPL than a voltage-driven receiver at a given distortion level.

In fig. 2, the output distortion is determined by the different characteristics of the receiver over different operating areas, depending on the coil current related to the output SPL. In general, higher coil currents produce more flux in the reed, thereby producing more reed deflection and corresponding motion of the diaphragm resulting in a higher acoustic output SPL. In fig. 2, the operating region is depicted as hysteresis, runaway, and saturation. These areas are primarily related to the flux in the reed. In the saturation region, the permeability in the armature is low and changes rapidly, so the output distortion increases rapidly. In order to keep the output distortion at or below a specified maximum (e.g., five percent (5%)), the coil current must be maintained at or below a certain level. However, reducing the coil current may result in a significant reduction in SPL. In the runaway region, the permeability is higher than in the saturation region, and the attraction force between the reed and magnet generally increases as the deflection reed moves closer to the magnet. Thus, as the space between the reed and the magnet is reduced, the reed tends to deflect more. If the magnetic force is stronger than the total mechanical restoring force of the receiver (i.e. the restoring force of the reed, diaphragm and other parts of the receiver), the magnetic force will deflect the reed towards the magnet and the reed may eventually stick to the magnet. As shown, run away is a major source of non-linearity at moderate drive levels. At lower coil current levels, the non-linearity caused by hysteresis is dominant.

The output distortion of the acoustic transducer or receiver is reduced using a feed-forward algorithm that applies a pre-distorted electrical excitation signal to the input of the receiver. The feed forward system may be open or closed. In an open system, a predistorted electrical excitation signal is applied to the input of the receiver without adapting the predistortion to changes in the characteristics of the receiver. In a closed system, information indicative of changes in receiver characteristics is used to adaptively update a calculable nonlinear function used to predistort an input signal. The feedforward system uses an inverse model to generate a pre-distorted electrical excitation signal. The inverse model may be created by testing or by numerically inverting the forward model. The inverse model can be efficiently implemented using non-linear polynomials, in addition to other calculable non-linear functions. These and other aspects of the disclosure are further described herein.

The pre-distorted electrical excitation signal is the output of a calculable nonlinear function of an electrical input signal (x) representing the desired acoustic output. For armature-based receivers, the pre-distorted electrical excitation signal compensates for non-linearities attributable to mechanical and hysteresis, runaway and saturation, and other sources.

In fig. 1, the system includes an input signal source 102, an input signal predistortion circuit 104, a battery or power supply 106, an armature based receiver 108 having nonlinear transfer characteristics, and an acoustic load 110. The load represents the user's ear and any interconnecting structures (e.g., sound tube, coupling means, and leaks and ventilation). The acoustic load may vary depending on the particular type and application or implementation of the receiver. The driver circuit 116 provides a pre-distorted electrical excitation signal to the receiver. The input signal source provides an electrical input signal representing a desired acoustic output signal. The input signal may be an analog signal or a digital signal. In embodiments where the predistortion is performed by a digital processor, the analog input signal will be converted to a digital signal. The input signal predistortion circuit 104 includes an algorithm that generates a predistorted electrical excitation signal for an electrical input signal as discussed herein. The algorithm may be implemented at least in part as computer instructions executed by processor 112 or by one or more separate equivalent circuits. The algorithm includes a partial or complete inverse model that describes how the input signal must be modified to achieve the desired output for a particular receiver or for a particular class of receivers. The inverse model may be based on empirical data obtained from actual receivers or from models of receivers or a class of receivers. Alternatively, the inverse model may be based on a forward model as follows: the forward model predicts the receiver outputs for a given input to the receivers. The forward model can be inverted by computational techniques to create an inverse model directly. The algorithm and any model of the receiver may be stored in the memory means 114 associated with the receiver. The driver circuit 116 may be collocated with the processor and memory device on a common integrated circuit, as shown, or the driver circuit may be a separate or discrete entity from the predistortion circuit.

In fig. 1, the input signal source 102 may be any acoustic signal source. In one embodiment, the input signal is obtained from a microphone (e.g., a capacitive microphone such as an electret or microelectromechanical system (MEMS) microphone) or from a piezoelectric device or some other acoustic transduction device. The microphone may be part of: a hearing aid, an earphone, a wearable device or some other system with which an acoustic receiver or receiver is integrated to communicate. Alternatively, the input signal may be obtained from a media player or from some other source internal or external to the system. The battery 106 may be needed in implementations where portability is desired (e.g., the receiver forms part of a consumer wearable product such as a hearing aid, wireless headset and earpiece, and other products). The input signal predistortion circuit 104, including the driver circuit 116, may be integrated with the armature based receiver 108 or with some other portion of the system into which the receiver is integrated. Some implementation examples are discussed below.

Fig. 3A-3D illustrate the output of an acoustic receiver responsive to a sinusoidal electrical input signal without predistortion compared to the receiver output responsive to a sinusoidal electrical input signal subject to predistortion using a calculable nonlinear function as further described herein. Applying a sinusoidal electrical input signal 132 to the input of the armature-based receiver 108 results in a distorted acoustic signal 138 at the receiver output. Using a calculable nonlinear function to predistort a sinusoidal electrical input signal 132 and applying the predistorted electrical input signal 134 to an armature-based receiver 108, a relatively undistorted acoustic signal 136 can be produced at the receiver output. Although the output signal may have some distortion, it will have less distortion than the output signal.

Fig. 4 illustrates various graphs of THD versus SPL for an armature-based receiver driven by an electrical excitation signal with and without predistortion. While 400Hz data is shown, other frequencies or ranges may alternatively be used. Curve 402 represents the THD versus SPL for an input signal having a frequency of 400Hz applied to the receiver through a current amplifier, where the input signal is not pre-distorted. Curve 404 represents the THD versus SPL for an input signal having a frequency of 400Hz applied to the receiver by a constant voltage amplifier, where the input signal is not pre-distorted. The voltage amplifier has a relatively low output impedance relative to the armature-based receiver, and the current amplifier has a relatively high output impedance. Many devices, particularly portable electronic devices, are in an intermediate state if the output impedance is in the same order of magnitude as the impedance of the armature receiver. Curve 406 represents the THD versus SPL for a predistorted input signal having a frequency of 400Hz applied to the receiver by a constant current amplifier. Fig. 4 illustrates that the SPL of curve 406 is increased by about 3 decibels (identified as improved SPL 408) relative to the SPL of curve 404 for five percent (5%) THD. Curve 406 shows that the receiver starts to saturate at higher input current levels (corresponding to higher output SPL) when the excitation signal is pre-distorted.

Fig. 5 illustrates various graphs of THD versus SPL for over-magnetized and non-over-magnetized armature-based receivers driven by excitation signals with and without pre-distortion. While 400Hz data is shown, other frequencies or ranges may alternatively be used. Curve 502 represents the THD versus SPL for an input signal having a frequency of 400Hz applied to the receiver by a constant current amplifier without pre-distortion and without the receiver being over-magnetized. Curve 504 represents the THD versus SPL for an input signal of 400Hz applied to the receiver by a constant voltage amplifier, without the input signal being pre-distorted and the receiver not being over-magnetized. Curve 506 represents the THD versus SPL for an input signal with no predistortion and a frequency of 400Hz applied to the receiver through a constant current amplifier, where the sensitivity of the receiver is increased by 1.5 db due to excessive magnetization. Curve 508 represents the THD versus SPL for a predistorted input signal of 400Hz frequency applied to the receiver by a constant current amplifier, where the sensitivity is increased by 1.5 db due to excessive magnetization. Fig. 5 illustrates that for five percent (5%) THD, the output SPL of curve 508 is increased by about 4 decibels (identified as improved SPL 509) relative to the output SPL of curve 504. Curve 508 shows that when the excitation signal is pre-distorted, the receiver starts to saturate at a higher input current level (corresponding to a higher output SPL) despite being over-magnetized and despite being driven by a relatively constant current amplifier. This result is in contrast to the results implied by curves 502 and 506, which curves 502 and 506 show the tendency of the output SPL to decrease when the receiver is driven by a constant current amplifier or when the receiver is over-magnetized, respectively.

Fig. 6 is a graph of the output SPL of an armature based receiver versus frequency for different types of drive signals. Curve 602 represents SPL versus frequency when the receiver is driven by a constant current source, and curve 604 represents SPL versus frequency when the receiver is driven by a constant voltage source. The frequency response of the output 602 produced by the current source is generally flatter than the output 604 produced by the voltage source. At frequencies above about 500Hz, fig. 6 also illustrates that the SPL is greater when the receiver is driven by a constant current source as compared to when the receiver is driven by a constant voltage source. The

first peaks

603 and 605 represent the main mechanical resonant frequencies of the

respective curves

602 and 604. The other peaks represent other resonance frequencies of the receiver. The main mechanical resonance frequency of the receiver depends on the mechanical stiffness of the system (e.g. reed and suspension in an armature based receiver) and the moving mass of the mechanical system (e.g. reed, diaphragm, drive rod and suspension in an armature based receiver). More specifically, the resonance frequency is proportional to the square root of the ratio of the mechanical stiffness k and the moving mass m (sqrt (k/m)). In FIG. 6, the main mechanical resonance of curve 602 is about 1700Hz, and the main mechanical resonance of curve 604 is about 1900 Hz. In general, a higher negative stiffness tends to lower the resonant frequency of the receiver, while an increased mechanical restoring force (i.e., positive stiffness) of the receiver tends to increase the resonant frequency of the system. Negative stiffness refers to the tendency of the magnetic force to counteract the mechanical restoring force of the reed.

Typically, the pre-distorted electrical excitation signal is generated by applying an electrical input signal (x) representing the desired acoustic output to a computable non-linear function before applying the pre-distorted electrical excitation signal to the acoustic receiver. The function modifies the input signal to provide a desired acoustic output at the acoustic output port of the receiver. The function that can be calculated is the following function: for this function, there is an algorithm that produces a function output for a given input within the function domain. The calculable non-linear function may be implemented as a continuous function or a piecewise linear function. The piecewise linear function may be based on a look-up table in which linear interpolation is used to identify values between data points in the table. Other curve fitting schemes may be used to generate linear or non-linear functions that approximate the following data sets: the data set represents an inverse model adapted to distort the input signal.

In one embodiment, the calculable nonlinear function is any function that can be approximated by a rational polynomial. These functions include polynomials, hyperbolic and inverse hyperbolic functions, logarithmic and inverse (inverse) logarithmic functions, and other functional forms. Such asAs is generally known, these and other functions may be approximated by a sum of a finite set of terms having odd or even indices (e.g., truncated taylor series). Rational polynomials and polynomial functions are easily and efficiently implemented by digital processors. In other embodiments, other calculable non-linear functions may be used. Such other functions may have a negative exponent, an exponent less than unity or a non-integer exponent, a set of orthogonal functions, an inverse sigmoid form, or some other form. Thus, many suitable functional forms will include at least one and xⁿA proportional term where n is not equal to unity or the value of 1 (1). The form of the calculable nonlinear function and its parameters (e.g., terms, orders, coefficients, etc.) required for adequate compensation will depend in part on the particular receiver, the particular application or use case, and the desired output.

In one embodiment, the non-linear function is a polynomial having the general form:

＝k₁x+k₂x²+k₃x³+…+k_nxⁿ＝k₁x+k₂x²+k₃x³+…+k_nxⁿ

y＝k₁x+k₂x²+k₃x³+…+k_nxⁿformula (1)

In equation (1), the variable x is an electrical input signal representing a desired acoustic signal, and the function parameter is a coefficient. The electrical input signal may originate from a microphone associated with the hearing aid, from an audio source such as a media player, or from any other source. Coefficient k_nA constant representing the nth order (order) term in the series. The signal resulting from the sum of the terms is nonlinear and, as described below, the terms and polynomial coefficients are selected to compensate for the nonlinearity of the acoustic receiver. The odd-order terms typically compensate for symmetric nonlinearities, and the even-order terms typically compensate for asymmetric nonlinearities. Thus, the polynomial of equation (1) compensates for the symmetric nonlinearity and the asymmetric nonlinearity. In armature-based receivers, the symmetric non-linearity can be attributed to magnetic saturation of the receiver, air noise, receiverMicrophone suspension, and other characteristics, and asymmetric non-linearities can be attributed to reed imbalance, microphone suspension, and other microphone characteristics.

The polynomial of equation (1) most effectively compensates for non-linearity at frequencies below the main mechanical resonance of the receiver where the frequency response is substantially flat (as shown in fig. 6). Also, the sensitivity of the receiver with respect to the input current is similar under the primary resonance. In other words, the coefficient in equation (1) is effective in reducing distortion associated with frequencies below the main mechanical resonance of the receiver. For frequencies above the main resonance, the coefficients in the polynomial of equation (1) depend more strongly on the frequency. The generalization of equation (1) is to replace the coefficients in equation (1) with a frequency dependent transfer function (e.g., a time domain filter) as follows:

y＝(h₁(x))+(h₂(x))²+(h₃(x))³+…+(h_n(x))ⁿformula (2)

In the formula (2), h_n(x) Is a time domain filter, wherein the filter h₁(x) Is applied to a filter h₂(x) Square of the output of (a) and a filter h₃(x) And so on, with filter power being applied on a per sample basis. It will be appreciated that a special case of equation 2 is that one or more of the time domain filters are identical. In this case, the efficiency can be achieved by: the input signal is processed only once through the same filter and then the outputs are simply exponentiated to different degrees before addition. Equation (2) extends the applicability of polynomial based compensation to higher frequencies.

Equation (2) may be implemented using an autoregressive moving average (ARMA) filter. The ARMA filter is a digital filter that uses the current and past values of the input signal and the past value of the output signal to calculate the current output signal. The same input is applied to each filter, but the filter outputs are different, at least in part due to the order of the terms. A typical ARMA filter implementation is as follows:

y[n]＝b₀x[n]+b₁x[n-1]+b₂x[n-2]+a₁y[n-1]+a₂y[n-2]formula (3)

In formula (3), x [ n ]]Is the filter input, yn]Is the filter output, and constant a_nAnd b_nIs a filter parameter, where n is 0, 1, 2.

For many applications, a polynomial with a frequency independent term (as in equation (1)) will provide a fairly good compensation for receiver non-linearity, since most of the energy in the input signal is below the main mechanical resonance of the receiver. In one particular implementation, the nonlinearity of the armature-based receiver is compensated by modifying the electrical input signal applied to the receiver coil by a current amplifier having the following polynomial:

y＝k₁x+k₃x³+k₅x⁵+…+k_2n+1x²ⁿ⁺¹formula (4)

In equation (4), the variable x represents the electrical input signal, which represents the desired acoustic output. Coefficient k of odd order term_nThe principal component that compensates for the non-linearity of the receiver is mainly at frequencies below the main mechanical resonance of the receiver. As discussed, the odd-order terms (e.g., the first, third, and fifth order terms in equation (4)) compensate for the symmetric nonlinearity of the acoustic receiver. In armature-based receivers, the symmetry nonlinearity can be attributed to magnetic saturation, among other characteristics, some of which have been discussed above. Therefore, the polynomial in the equation (4) compensates for the nonlinearity in the saturation region illustrated in fig. 4. The polynomial of equation (4) will provide quite effective compensation, especially at higher amplitudes or higher amplitude drive levels. For some armature-based receivers, the coefficients of the even-order terms will be small or negligible. In some implementations, higher order terms may be eliminated with less, but still significant, improvement. In other implementations, the compensation may be improved by adding one or more additional terms to the polynomial. Fig. 7 illustrates a graph of an odd polynomial expressed by the following equation (5):

y＝0.28x+0.63x³+0.10x⁵formula (5)

Where y is "output" and x is "input".

Typically, the computable non-linear function is selected and optimized for a particular receiver or for a class of receivers and, in some implementations, for a particular processor. The term "optimization" or variations thereof as used herein means that when the receiver is driven by an electrical input signal that is predistorted by a function, selecting a calculable nonlinear function or parameters of such a function tends to reduce the output distortion of the receiver at a given SPL as compared to the output distortion that would be obtained at the given SPL if the receiver were driven by an electrical input signal without predistortion. Alternatively, optimization may also mean: selecting a computable non-linear function or parameters of such a function tends to increase the output of the receiver SPL for a specified distortion level when the receiver is driven by an electrical input signal that is pre-distorted by the function, compared to the SPL that would be obtained at the specified distortion level when the receiver is driven by an electrical input signal without pre-distortion. Optimization may also mean the selection of a calculable non-linear function or parameters of such a function that satisfy power consumption or processing and memory resource utilization constraints, among other considerations.

The optimization of the computable non-linear function may take many forms, including selecting a functional form or selecting one or more of the functional parameters. Polynomial functions can be efficiently calculated and the choice of the form of the non-linear function that can be calculated (e.g., odd or even order polynomial, approximate hyperbolic function.) can be dictated at least in part by the receiver type or the primary distortion (symmetric, asymmetric, or both) that needs to be compensated. Optimization may also be performed by selecting a set of one or more parameters of the non-linear function that may be calculated. In embodiments where the computable non-linear function is approximated by a summation of a series of terms, the function may be optimized by selecting the order or coefficient of the function. These optimized forms can be easily and efficiently implemented using a digital processor, for example, by implementing one or more iterative algorithms, examples of which are described below.

In some embodiments, the non-linear function that can be calculated (e.g., the polynomial in the above example) is determined experimentally or using a numerical model of the acoustic receivers. A mathematical algorithm or some other iterative scheme may be used to select the form of the non-linear function that can be calculated and to select the parameters of the function. Typically, the form of the non-linear function that can be calculated is first selected. Trial and error methods can be used to select a calculable nonlinear function that best compensates for the dominant distortion in a particular type of receiver or for a particular use case. This method can be implemented by generating a pre-distorted excitation signal using different non-linear functional forms, applying the pre-distorted excitation signal to the receivers, and evaluating the receiver outputs. Machine learning techniques or other mathematical algorithms are suitable for this purpose and may be used to facilitate form selection. The functional form that results in the most desirable receiver output can be selected. In addition to distortion compensation efficacy, the functional form may be selected based on processor or memory resource requirements. Constraints may be imposed to ensure that the selection of the function does not lead to undesirable results.

After selecting the form of the computable non-linear function, the function parameters can be selected or optimized by an iterative process to improve the performance of the receiver. For a non-linear function comprising the sum of a series of terms, the order and coefficients of the terms in the series, as well as other parameters, may be optimized by one or more iterative processes. To optimize the set of one or more parameters of the computable nonlinear function, the known input signal (e.g. a sinusoid) is predistorted using a previously selected nonlinear function with an initial set of parameters. For example, the initial set of parameters may be coefficients or exponents of a polynomial of equation (5). The initial set of parameters used during the first iteration may be based on best guesses, empirical data, or parameters previously used for similar listeners. The predistorted excitation signal is then applied to the input of the receiver or to a digital model of the receiver and the distortion of the resulting acoustic output of the receiver is then evaluated. In subsequent iterations, a new set of intermediate parameters is selected or determined based on the output distortion. The process iterates by incrementally changing one or more parameters of the selected function based on a measure of output distortion of the receiver until a desired output is obtained. Considerations other than receiver output may also be relevant to the selection of the function parameters. For example, the number of terms in a functional form or series may affect the computational load on processing and memory resources. Additional terms in the series may provide a more linear output or may be used to reduce clipping of the amplifier. Therefore, constraints may be imposed to ensure that the selection of the function parameters does not lead to undesirable results.

The distortion of the acoustic output of the receiver can be determined using known techniques. For example, the distortion of the output signal may be estimated by calculating the Total Harmonic Distortion (THD) of the output signal. Another approach is to calculate the output THD + noise. Other distortion measures may also be used. Algorithms implementing these and other techniques for determining distortion or linearity of an output signal are well known and will not be discussed further herein.

One such iterative method suitable for selecting or optimizing the parameters of a calculable nonlinear function is a gradient descent algorithm. Other algorithms may also be used. These algorithms typically converge to a local minimum of the function. A minimum is identified when the rate of change of the output signal distortion with respect to certain functional characteristics is close to zero. However, in some implementations, it may not be necessary to iterate to a minimum. For example, the non-linear function may be optimized for a specified distortion level without reaching a local minimum. The optimized function or the set of parameters associated with the function may be stored in a memory device associated with the acoustic receiver for subsequent use.

The optimization of the calculable nonlinear function may be performed by the testing system after the acoustic receivers are manufactured, as discussed in connection with the system 800 of fig. 8. However, in other embodiments, the optimization is implemented by a processor or integrated circuit associated with the handset, as described below. The system 800 optimizes a calculable nonlinear function for acoustic receivers having initial operating characteristics or for receivers or a class of receivers having initial characteristics. System 800 includes a function or inverse model generator 802 that optimizes a calculable nonlinear function until the output distortion of the receiver satisfies a criterion (e.g., a specified output distortion level). As suggested above, the inverse model generator may select the form of the non-linear function that may be computed or select the parameters of the function or both. As discussed above, the method for selecting the functional form is generally different from the method for selecting the parameters of the function. The system 800 further comprises a pre-distorted excitation signal generator 804 that generates a pre-distorted electrical excitation signal by applying an input signal representing a desired acoustic output to the non-linear function generated by the inverse model generator. The input signal is generated or provided by an input signal source 806. The input signal may be a sinusoidal test signal. During optimization, the pre-distorted electrical excitation signal is iteratively applied to the receiver 810 and the function is iteratively updated based on an iterative measure of output distortion until the output distortion of the receiver meets a certain criterion.

In fig. 8, a pre-distorted electrical excitation signal is applied by a current or voltage amplifier 808 to a receiver 810. The acoustic output of the headphones is input to an acoustic test load 812, which acoustic test load 812 models the acoustic load of the headphones. Such loading may represent the sound tube, the user's ear anatomy, sound leakage, and other loading variables, some of which are discussed elsewhere herein. The microphone converts the acoustic output signal into an electrical signal that is fed back to the distortion calculator 816. The microphone may be part of the receiver or test load. As discussed above, the distortion calculator 816 calculates the distortion of the electrical signal provided by the acoustic test load 812. The result of the distortion calculation is provided to an inverse model generator 802 to optimize the nonlinear function in the next iteration. This process iterates until the receiver output meets specified criteria. After selecting or optimizing the calculable nonlinear function, the nonlinear function is stored on the earpiece or on a memory associated with the earpiece for subsequent use as discussed below.

In one implementation, the inverse model generator 802, the pre-distorted excitation signal generator 804, and the distortion calculator 816 are implemented by digital processing devices. Although the inverse model generator, the predistortion signal generator and the distortion calculator are schematically illustrated as separate functions, these functions may be implemented by executing one or more algorithms on one or more processors, schematically represented as processor 818. In some embodiments, the input signal used to optimize the non-linear function is also generated by the processor 818, and thus the input signal source 806 may also be implemented as a signal generation algorithm (e.g., a sine wave generator) executed by the processor. Alternatively, the input signal may be obtained from an external source.

In another implementation, the microphones 810 and acoustic test loads 812 of fig. 8 are represented by numerical models representing a particular microphone or class of microphones. The model is schematically illustrated at 814. According to this embodiment, the computable non-linear function is determined by iteratively applying the intermediate pre-distorted electrical excitation signal to a model of the receiver and the load. Model 814 outputs a signal representative of the acoustic output of the modeled earpiece in response to applying the predistorted input signal to the model. The output of the model 814 is provided to a distortion calculator 816 for analysis. The distortion calculator determines the distortion of the output signal fed back from the model and provides the result to the inverse model generator for the next iteration. In this embodiment, the amplifier 808 is a virtual device that may be implemented by the processor 818. The models 814 of the microphones and the load may also be implemented by the processor 818. Digital models based on similar electrical equivalents of receivers are generally known, and representative models of armature-based receivers are described below with reference to fig. 11A and 11B.

After the computable non-linear function is selected or optimized, the function is written to a memory device on or associated with the earpiece for ultimate use. The memory means may be a separate component or it may be part of an integrated circuit (e.g. ASIC) provided in or on the earpiece. The memory device or integrated circuit may also be located on another component used with the receiver or in or on a device or system integrated with the receiver. Such a device or system may be a hearing instrument, such as a pair of headphones or a hearing assistance device, among other examples discussed herein. In fig. 8, the processor 818 writes the calculable nonlinear function or function parameters to a memory device 822, which memory device 822 may be part of an integrated circuit 820 associated with the receiver.

In some implementations, the set of alternative parameters is determined for a different characteristic of the acoustic receiver than the initial characteristic. As discussed above, the alternative set of one or more parameters is optimized by iteratively applying the intermediate parameters to the receivers having different characteristics and evaluating the output distortion. A parametric model representing an alternative set of parameters is stored in a memory device associated with the receiver to anticipate changes in characteristics of the receiver when used by an end user. The parametric model typically associates the set of alternative parameters with information indicative of corresponding characteristics of the receiver. The alternative parameter set may be generated by the system 800 of fig. 8 or by a processor or integrated circuit associated with the handset discussed in connection with fig. 9. The parametric model may be implemented as one or more look-up tables or as one or more continuous or piecewise linear functions. According to this aspect of the disclosure, operating conditions indicative of changes in the characteristics or configuration of the receiver are monitored during operation of the receiver, in some cases using sensors located on or near the receiver. Upon detecting a condition indicative of a change in the ear piece characteristics, information indicative of the change is fed back to a processor associated with the ear piece, and the parameter is updated using the parametric model to compensate for the change. Some examples of using the alternative parameters are discussed below. More generally, the method can be used to select different non-linear functional forms or parameters of selected functions to compensate for variations in receiver characteristics.

In use, an acoustic receiver having a non-linear transfer characteristic is associated with an electrical signal conditioning device comprising a processor for generating a pre-distorted electrical excitation signal by applying an electrical input signal (x) representing a desired acoustic output to a computable non-linear function optimized for the receiver. As discussed above, the pre-distorted electrical excitation signal is the output of a non-linear function. In one implementation, the non-linear function includes a function of xⁿProportional at least one term, wherein n is not equal to unity. Generally, when applyingThe predistorted electrical excitation signal improves the performance of the receiver when input to the receiver with nonlinear transfer characteristics. In armature-based receivers, the acoustic output of the receiver is produced by deflecting the armature relative to one or more magnets when a pre-distorted electrical excitation signal is applied to the coil of the receiver. In one embodiment, for a specified distortion level, the sound pressure level of the acoustic output produced in response to the pre-distorted electrical excitation signal is greater than the sound pressure level that would be produced at the specified distortion level in response to the electrical excitation signal without pre-distortion. In another embodiment, the acoustic output produced in response to the pre-distorted electrical excitation signal has less distortion than the acoustic output produced in response to the electrical excitation signal without pre-distortion for a given acoustic sound pressure level. In other embodiments, the pre-distorted electrical excitation signal provides some other benefits, such as efficient processing and memory resource utilization.

Fig. 9 illustrates an Integrated Circuit (IC)900 for use in conjunction with an acoustic receiver. Although fig. 9 illustrates different features and functions on a single circuit (e.g., ASIC), in alternative implementations, these features and functions may be performed by multiple circuits. One or more discrete circuits or ASICs are located in or on the handset or system integrated with the handset, examples of which are discussed herein. The IC includes an external device interface 902 that enables communication between the receiver and external devices (e.g., the system 800, hearing aid circuitry of fig. 8, and circuitry of an audio headset and other audio systems integrated with the receiver). For example, the system of fig. 8 may transfer computable nonlinear functions, function parameters, parametric models, numerical models of microphones, and other information to the memory device 922 via the external device interface 902 in fig. 9. The input signal representing the desired acoustic output may also be communicated to the integrated circuit via an external device interface prior to generating the pre-distorted electrical excitation signal. Such an input signal may originate from a microphone or from a media content source or from some other audio signal source. The integrated circuit may also transmit information to the headphones or other circuitry of the system with which the headphones are integrated via the external device interface. For example, the hearing instrument may have a separate processor in communication with the integrated circuit 900. External device interface 902 also represents signal conditioning that may be performed on signals received by integrated circuit 900 and transmitted from integrated circuit 900. Such conditioning may include analog-to-digital A < - > D conversion, signal format conversion (e.g., PDM < - > PCM), and other signal conditioning.

Fig. 9 also illustrates a pre-distorted excitation signal generator 924 that generates a pre-distorted electrical excitation signal by applying an input signal representing the desired acoustic output to a computable nonlinear function. The predistortion excitation signal generator 924 of fig. 9 is similar to the predistortion excitation signal generator 804 of the system of fig. 8. As suggested, an input signal representative of a desired acoustic output may be input by other circuitry of a device or system integrated with the microphone at external device interface 902. In fig. 9, the pre-distorted electrical excitation signal is provided to an amplifier 926 for subsequent input to the receiver. The amplifier 926 is shown as part of an integrated circuit, but in other embodiments the amplifier may be a discrete circuit or device disposed between the integrated circuit and the receiver. The amplifier may be implemented as a voltage amplifier or a current amplifier. The current amplifier may be implemented as a current input/current output amplifier or a transconductance amplifier having a voltage input and a current output.

In some embodiments, a processor associated with the receiver generates an updated calculable nonlinear function to accommodate changes in the characteristics of the receiver. The non-linear function is updated with an alternative set of parameters. For this purpose, conditions of the receiver indicative of a change in the characteristic are sensed and information indicative of the change is fed back to the processor. This condition of the receiver can be detected by monitoring or sensing changes in the receiver impedance, front volume pressure, back volume pressure, receiver output SPL, and other detectable conditions of the receiver. The processor generates an updated non-linear function, for example, by applying the updated set of parameters to the non-linear function.

In fig. 9, for example, an integrated circuit 900 associated with the ear piece includes a feedback interface and conditioning circuit 928 to receive information from the ear piece. The feedback interface and conditioning circuitry 928 also represents signal conditioning that may be performed on the signals from the microphones, including a/D conversion, signal format conversion, and other signal conditioning. The feedback interface and regulation circuit 928 is shown schematically separately from the external device interface 902, but in other embodiments these interfaces may be implemented as a common interface. The feedback interface is coupled to a processor 930, the processor 930 evaluating the receiver feedback and determining an updated non-linear function using the model stored in the memory 922. The updated non-linear function is also stored in the memory.

Fig. 10 is a schematic block diagram of an armature-based receiver 1000, the receiver 1000 comprising a coil 1002 disposed around a portion of an armature 1004. The armature has a movable portion 1006 that deflects between the magnet 1008 and the magnet 1010 when an excitation signal is applied to the coil. The magnet is held by a yoke 1012. The movable portion of the armature is coupled to the diaphragm 1014 by a linkage 1016. The diaphragm is hinged or otherwise movably coupled to a support structure 1015 held by the receiver housing 1018. The flexible membrane 1019 bridges the gap between the diaphragm and the support structure, and the combination forms a diaphragm. The diaphragm divides the housing 1018 into a front volume 1020 and a back volume 1022. Deflection of the armature causes the diaphragm to move, resulting in a change in air pressure in the front volume, where acoustic pressure (e.g., sound) is emitted through the output port 1024 of the receiver. The schematic receiver diagram of fig. 10 represents any armature-based receiver configuration. For example, other receivers may have different armature or yoke configurations as well as other configurations.

As suggested above with reference to fig. 9, in some embodiments, the headphones provide information about the varying configuration or characteristics of the headphones for which it may be desirable to update the non-linear function used to pre-distort the input signal. Some of these varying characteristics can be detected by monitoring the condition of the receiver with sensors on the receiver or in an integrated circuit (e.g., the circuit of fig. 9). For example, the impedance of the receiver may be monitored by a sensor in the amplifier circuit or other circuitry. However, monitoring for other conditions may require additional sensors on the receiver (also referred to as an electroacoustic transducer or microphone). In fig. 10, for example,

microphones

1026 and 1028 may be used to monitor changes in air pressure in the front and rear volumes of the housing, and microphone 1030 may be used to convert the acoustic output of the receiver into an electrical signal that may be analyzed for distortion and for other characteristics as described below. Information from the headphones indicative of these and other varying headphone characteristics is schematically illustrated in fig. 9 at headphone feedback information 936. Some specific examples are discussed below.

As suggested above, some or all of the functionality of the circuit of fig. 9 may be implemented in a microphone or in some other part of a system in which the microphone is integrated. Fig. 13 shows a receiver 1300 having an integrated circuit implemented as an ASIC1302, the ASIC1302 being disposed within a back volume 1304 of the receiver housing. More generally, the receiver 1300 may have some other form. In other embodiments, some or all of the circuit functions may be provided in some other part of a device or system that is integrated with the receiver. In a hearing aid implementation, for example, an integrated circuit 1306 having some or all of the functionality of the circuitry of fig. 9 may be provided in the behind-the-ear (BTE) unit 1308. In other embodiments, some or all of these circuits may be provided in the housing of the headset or in a portion of some other system that is integrated with the receiver.

One condition that can affect the output of the receiver is a change in the initial steady-state (i.e., rest) position of the reed between the magnets. The initial rest position of the reed is typically a balanced position, but in some embodiments it may be unbalanced. This change in the resting position of the reed can be due to a bump or other impact on the receiver. As discussed above, it may be desirable to update the non-linear function that can be calculated to accommodate changes in the resting position of the reed. One approach, among others, is to update the function by applying an alternate set of parameters to the function. Table 1 below shows the identified location x of the reed₀Of initial rest positionAn initial set of polynomial coefficients. According to this example, the relative to the initial rest position (i.e., x) may be targeted₀) Different reed rest positions (e.g., +/-x)₁、+/-x₂....) to calculate an alternative optimized parameter set. Alternative parameters can be calculated by the system of figure 8 for different reed rest positions using the iterative method described herein. Different reed rest positions can be obtained by applying different +/-DC biases to the magnetic circuit of the receiver. Alternatively, the alternative parameter set may be determined by iteratively applying the intermediate pre-distorted excitation signal to a receiver model with different reed rest positions using a virtual amplifier. The optimized set of replacement parameters can be tabulated for each reed position as follows:

TABLE 1

In general, there may be more or fewer parameter sets than illustrated in table 1, depending on the particular non-linear function implemented. For example, equation (4) above only requires the calculation of the coefficients of the first order term, the third order term, and the fifth order term. In some embodiments, the data of table 1 is stored as a look-up table in the memory of the handset. The listener processor may then reference the look-up table to determine an updated set of parameters based on the detected change in the resting position. The updated parameters may then be applied to a non-linear function for pre-distorting the input signal. In some embodiments, the algorithm implementing the look-up table includes an interpolation function that calculates a set of parameters of reed rest positions between the rest positions at which the tabulated data is determined. The algorithm implementing the look-up table may also include an extrapolation function that calculates a set of parameters that exceeds the rest position of the reed that determines the location of the tabulated data. The interpolation and extrapolation functions may be based on linear or non-linear approximations relative to tabulated data points.

In other embodiments, the alternate parameter set of Table 1 can be used to form one or more mathematical functions that model the relationship between the reed rest position and the corresponding function parameter set. The functional model may be a single function or a collection of piecewise linear or nonlinear functions. For example, a separate function or set of functions can be used to model each parameter as a function of the reed rest position. Such functions may be generated using known curve fitting techniques such as regression analysis or other function approximation methods. As with the look-up table, these function models can be stored on the receiver for updating the parameter set when a change in the stationary position of the reed is detected. Where a mathematical function is used to model the relationship between the reed rest position and the sensed information indicative of changes in the reed rest position, it may not be necessary to use interpolation or extrapolation algorithms. A look-up table or function associates information from the receiver (e.g., impedance, strain, pressure) representing changes in the resting position of the reed with a corresponding set of parameters.

Changes in the rest position of the reed (also known as changes in the balance of the receiver) can be detected directly or indirectly. In one implementation, the change in the resting position of the reed is detected by monitoring the change in the impedance of the receiver. The receiver impedance can be directly detected by the measurement at the receiver coil. Alternatively, a reed strain gauge can be used to monitor changes in the resting position of the reed. Figure 10 illustrates a strain gauge 1032 provided on a portion of the reed 1004 for this purpose. Changes in the resting position of the reed can also be monitored by measuring changes in the air pressure of the receiver using one or more pressure sensors (e.g., microphone 1026 in the front volume, microphone 1028 in the back volume) or using pressure sensors in the front and back volumes. Thus, table 1 above or any corresponding function may associate a set of substitution coefficients or other function parameters with any of these detectable conditions.

Another situation that may affect the output of a receiver is a change in the frequency response of the receiver. This variation can be attributed to the hearing instrument (e.g. hearing aid, ear)Machine, etc.), cerumen accumulation in the acoustic passages of the hearing aid, and other changing characteristics of the receiver or system that occur during use. As suggested above, the initial frequency response f for the receiver₀An optimized initial set of parameters is calculated. An alternative set of parameters may also be determined for different frequency responses of the receivers. For example, the frequency response may be changed by incrementally changing the acoustic leakage of the test load, and a new set of parameters may be calculated for each incremental change. An alternative set of parameters may also be determined for incremental changes in acoustic blockage corresponding to wax (wax) accumulation in the hearing aid. The frequency response of the receiver can also be changed based on other changing characteristics of the receiver and an alternative set of parameters can be determined accordingly. Similar to the example above, the replacement parameter set is iteratively optimized for each incremental change of actual receivers. Alternatively, models of the receiver and the load are used to optimize the alternative parameter set. The set of alternative parameters optimized for different frequency responses of the receivers can be tabulated as follows:

TABLE 2

In general, there may be more or fewer parameter sets than illustrated in table 2, depending on the function implemented (e.g., whether the function is odd or even). In some embodiments, the data in table 2 is stored as a look-up table in the memory of the handset. The look-up table may then be used by the microphones to determine updated parameters based on detected changes in various microphone characteristics (including load characteristics) indicative of changes in frequency response. In some embodiments, as described above, the algorithm implementing the look-up table includes an interpolation or extrapolation function that calculates a set of parameters for determining changes in frequency response between or outside the locations of tabulated data. In other embodiments, the parameters in table 2 are used to formulate one or more mathematical functions that model the relationship between the frequency response and the information indicative of changes in the characteristics of the receiver. For example, a separate function may be used to model each parameter as a function of the frequency response. Such a functional model may be generated using known curve fitting techniques such as regression analysis or other functional approximation methods as discussed above. As with the look-up table, these functions may be stored on the handset for updating parameters when conditions are detected that indicate a change in frequency response. Changes in the receiver frequency response can be detected by monitoring changes in the resonance peak and other characteristics of the frequency response. In one embodiment, the frequency response of the receiver is monitored using a Fast Fourier Transform (FFT) or Discrete Fourier Transform (DFT) applied to an electrical signal representing the output of the receiver. The electrical signal may be generated using a microphone provided at an output of the receiver. Fig. 10 schematically illustrates a microphone 1030 that is located just outside or inside the output port of the receiver for this purpose. Another approach is to apply a test signal at the resonant frequencies of the receiver and measure the amplitude of an electrical signal representing the output at one or more resonant frequencies. A look-up table (e.g., table 2 above) or a functional model may be used to associate a set of parameters with the FFT or DFT output or other sensing condition indicative of a change in frequency response. In some embodiments, it may be desirable to control the amplifier output to change the characteristics of the receiver. For voltage-driven receivers, it may be desirable to adjust the output (e.g., amplitude or phase) of the voltage amplifier to compensate for the varying impedance of the receiver. For example, the amplitude or phase of the voltage amplifier output may be adjusted as the receiver impedance changes to provide a more constant current level or to control the phase of the amplifier output signal. The receiver impedance can be measured directly at the receiver coil and the sensed change can be used to control the voltage of the amplifier. For current amplifier driven receivers, it may be desirable to adjust the output (e.g., amplitude or phase) to compensate for varying receiver characteristics. In fig. 9, processor 930 uses adjustment circuit 932 to adjust or compensate the output of amplifier 926 based on the changing microphone characteristics indicated by microphone feedback information 936. In battery powered devices, a battery provides power to a conditioning circuit. The conditioning circuit 932 may also include voltage regulators, charge pumps, and other power supply conditioning circuits. In one embodiment, the non-linear function or parameters of the function that may be calculated are selected by circuitry associated with the earpiece system, rather than by a test system like system 800 of FIG. 8. In accordance with this aspect of the disclosure, the functions of the input signal generator 806, the distortion calculator 816, and the inverse model generator 802 of fig. 8 are implemented by a processor associated with a microphone. For example, the functionality may be implemented by one or more processors of the integrated circuit 900 of fig. 9. A sensor at the output of the receiver may provide output signal distortion feedback from which the initial calculable nonlinear function may be updated. So configured, a processor associated with the receiver may generate and optimize a non-linear function for the initial characteristics of the receiver or for subsequent characteristics of the receiver by applying a pre-distorted test signal to the input of the receiver and implementing one of the iterative processes discussed herein until a desired output distortion level is obtained. The non-linear function can be optimized from time to adapt or compensate for variations in the initial characteristics of the receiver. Implementing nonlinear function optimization on a processor associated with a microphone may eliminate the need to perform some or all of the optimizations on the system 800 discussed above in connection with fig. 8. Fig. 11A and 11B are schematic representations of equivalent circuit models of a receiver that can be implemented digitally. The model is based on an electrical analog (tec30033 voicenlb 1) with a signal source (sine generator 1) and a load (load2CC 1). This technique produces a linear model of the receiver. The model typically includes a current variable and a voltage variable. Such a model may be implemented by several business programs (e.g., SPICE). The numerical model is the transformation of the receiver part into the electrical domain, where mass is represented by an inductor, stiffness by a capacitor, loss by a resistor, acoustic cavity by a capacitor, acoustic length by an inductor, viscous damping effect by a resistor. In fig. 11A and 11B, pure magnetoresistance (e.g., saturation, gap, and leakage elements) is transformed or modeled as a capacitor. In the magnetic domain, reed saturation, negative stiffness, leakage and air gap are modeled along with losses caused by eddy currents. According to this model, a parameter describing the size of the capacitor (representing armature saturation) changes according to the magnetic flux density and is proportional to the magnetic permeability of the reed. The total flux is the sum of the flux generated by the coil and the flux from the magnet transferred into the armature as a function of position minus the flux loss due to leakage. The total flux divided by the cross-sectional area of the reed is the flux density, which can be converted to magnetic permeability by the function shown in fig. 12. The modeling of the receiver will perform substantially similar to a real device. The model may be used to determine the parameters using the iterative method described above. Second, since the equations are now described in the model, a detailed inverse model can be created. The inverse model may be applied directly to the input signal to produce a predistorted output.

Referring to fig. 9, 10 and 14, in this example, the integrated circuit includes a processor 930 that executes an acoustic load change determination algorithm 1400, which acoustic load change determination algorithm 1400 uses receiver feedback information 936, such as an electrical output signal proportional to the sound pressure of an acoustic signal from the front volume and/or the back volume of an acoustic receiver and/or an acoustic output channel, as described above. The acoustic signal is converted to an electrical output signal by the feedback interface and conditioning circuit 928 or may be accomplished by a microphone positioned to detect acoustic output in the front or back volume or acoustic channel. In one example, the electrical output signal is proportional to the sound pressure of the acoustic signal. The acoustic load change determination algorithm causes the processor to determine whether there is a change in the acoustic signal indicative of a change in an acoustic load coupled to the acoustic receiver by comparing the electrical signal to reference information. The change in the acoustic signal is indicative of, for example, a foreign particle blockage or acoustic leak or other condition. In one example, the reference information includes data stored in memory 922. In another example, the reference information is generated by a processor executing one or more functions.

Fig. 14 also illustrates that integrated circuit 900 may include or be coupled to a wireless transceiver 1402 to allow notifications, such as obtained diagnostic data or other information, to be remotely transmitted to a remote device 1404, for example, the remote device 1404 may be a mobile user device, such as a smartphone, a wearable device, or other mobile device. Additionally or alternatively, the remote device 1404 may be a cloud-based server or a diagnostic test system that may be configured to diagnose acoustic headphones. As shown, the hearing device may further comprise an input/output device 1406, such as an in-the-ear insertion sensor, which may be a capacitive sensor that detects that a hearing aid or hearing device has been inserted into or removed from the ear. Upon removal from the ear, a diagnostic operation to determine whether the acoustic load has changed may be automatically activated. Also, the selection of an appropriate desired transfer function may depend on whether the device is coupled. The acoustic device may include a visual output device, such as an LED, so that a user or technician may be visually notified of the sensed condition. In other embodiments, the circuitry may provide one or more audible tones or messages indicating a need for service based on the diagnostic result. The diagnostic data may also be stored in the memory of the circuit for later interrogation by a service technician. In other embodiments, other suitable input/output devices may be used to indicate the status of the acoustic device or to allow sharing of data on the device. Processor 112 may also function as a processor that serves as an acoustic load change determination circuit similar to processor 930 in fig. 9.

Fig. 15 illustrates one example of an algorithmic process or method for diagnosing changes in acoustic loading of a receiver such as the type shown in fig. 10. The method may be performed while the user is using the acoustic receiver, or may be performed while the acoustic receiver is in the test system. In fig. 15, in block 1500, the method includes generating an acoustic signal in response to an electrical input signal applied to an acoustic receiver. In one example, this is accomplished by the processor providing the drive signal as an electrical input signal to the acoustic receiver, examples of which are discussed herein. As shown in block 1502, the method includes converting an acoustic signal to an electrical output signal, such as receiver feedback 936, that is proportional to a sound pressure of the acoustic signal using an electro-acoustic transducer. This is accomplished in one example by one or

more microphones

1026, 1028, and 1030 shown in fig. 10. In fig. 15, in block 1504, the method includes determining, for example by the processor 930 of fig. 9, the processor 112 of fig. 14, or any other suitable circuitry, whether there is a change in the acoustic signal indicative of a change in the acoustic load coupled to the receiver. This may be done, for example, by comparing the electrical output signal to reference information stored in memory 922 or generated by processor 930 using a function. Since the processor provides an electrical input signal to the receiver and since the reference information can be used to indicate what is desired as an output of the expected transfer function or the reference transfer function, the processor can determine any change in the acoustic load. The expected transfer function (also referred to as sensitivity) of the receiver is substantially linear over a known operating range of the receiver (e.g., a relatively low to medium amplitude electrical input signal). These ranges are good input signals for generating the reference transfer function and for measuring during normal operation of the device to determine the change in the acoustic signal.

Fig. 16 illustrates an example method for an acoustic device that includes determining whether there is a change in an acoustic signal by comparing data representing a measured transfer function to data representing an expected transfer metric, as shown in block 1600. Data representing the expected transfer function is stored in memory or may be generated by a processor from a programmed function or a set of functions modeling the expected transfer function. As described above with respect to acoustic loading, reference loading information may be used to obtain data representing an expected transfer function. At block 1602, in some implementations, the method includes providing a notification when there is a change in the acoustic signal indicative of a change in the acoustic load. For example, the processor generates information for a cloud server at the headphones, at the acoustic device, or may store it in the device for later interrogation. The notification may include any suitable data. The determining operation may also be performed by a processor or other circuitry in any suitable device discussed herein.

Either or both of the blockage diagnostic processing in blocks 1604 and 1606 and the joint integrity processing in

blocks

1608 and 1610 may be performed. As shown in blocks 1604 and 1606, the step of determining whether there is a change in the acoustic signal includes determining whether there is an occlusion of an output of the receiver, wherein the expected transfer function is a ratio of a reference electrical output signal to a reference electrical input signal for a reference acoustic load representing the receiver that is not occluded. Reference loads indicating various levels of complete occlusion may also be used. As shown in

blocks

1608 and 1610, the step of determining whether there is a change in the acoustic signal includes determining whether there is a change in the acoustic leakage, wherein the expected transfer function is a ratio of the reference electrical output signal to the reference electrical input signal for the reference acoustic leakage or the sealed reference acoustic load.

The method may further comprise detecting the front volume sound pressure by converting an acoustic signal into an electrical output signal using an electroacoustic transducer positioned to sense sound pressure in a front volume of the receiver, wherein the receiver comprises an armature connected to a diaphragm that divides a housing of the receiver into the front volume and a back volume. The method may include detecting a back volume sound pressure by converting an acoustic signal into an electrical output signal using an electro-acoustic transducer positioned to sense sound pressure in a back volume of an acoustic receiver, wherein the receiver includes an armature connected to a diaphragm that divides a housing of the receiver into a front volume and a back volume. The method may include detecting acoustic pressure in the acoustic port by converting an acoustic signal into an electrical output signal using an electro-acoustic transducer positioned to sense acoustic pressure in the acoustic port, wherein the receiver includes an armature connected to a diaphragm that divides a housing of the receiver into a front volume and a back volume, and the receiver output includes an acoustic port acoustically coupled to the front volume.

The method may comprise detecting a front volume sound pressure below a resonance frequency by converting an acoustic signal into an electrical output signal using an electroacoustic transducer located in a front volume of the receiver, wherein the receiver comprises an armature connected to a diaphragm, the diaphragm dividing a housing of the receiver into the front volume and a back volume. As discussed herein, the resonant frequency may be a primary mechanical resonant frequency or an acoustic resonant frequency. Fig. 17 shows reference information corresponding to the maximum sound pressure of the receiver in the 12 db + reference SPL curve that the receiver can produce in the front volume without the receiver output being blocked. Any sound pressure detected in the front volume above the maximum sound pressure level indicates an acoustic blockage. The comparison at frequencies below the receiver resonance frequency may be most efficient, but the comparison of the output signal with the reference information may be performed at any frequency. Fig. 10 shows a microphone 1026 in the front volume, suitable for detecting acoustic output.

In fig. 10, the acoustic receiver 1000 is an armature-based acoustic receiver comprising at least one electro-acoustic transducer located in at least one of the front volume, the back volume and the output of the receiver. The circuit is operable to determine whether there is a change in an acoustic signal of the receiver based on the acoustic pressure sensed by the at least one electro-acoustic transducer, wherein the change in the acoustic signal is indicative of a change in an acoustic load coupled to the receiver. The circuit may be part of the receiver or some other part of the acoustic device integrated with the receiver.

As described above, only one pressure sensor may be employed, but a plurality of pressure sensors may also be employed as needed. For example, a transducer in the front volume or downstream of the front volume may be used for seal detection. The transducer in the back volume can better capture changes around the main mechanical resonant frequency. The transducers in the back volume are also better suited to accommodate predistortion. Processor 930 determines whether there is a change in the acoustic load by comparing the electrical signals from the respective sensors with reference information stored in memory. The reference information as described above may be any suitable reference information including, but not limited to, data representing one or more points along the frequency response curve, amplitude values at one or more frequencies, frequency of peaks or valleys, Q (quality factor), frequency variation with respect to expected frequency, or any other suitable information (see also fig. 17-19). In one example, integrated circuit 900 need not include predistortion operations.

As described above, when it is determined that there is a change in acoustic load in the output of the acoustic headphones, in one example, the processor 930 issues a notification of the change in acoustic load to an appropriate device, such as a visual indicator (e.g., an LED) on the hearing device itself, a message sent to the user's smartphone to cause an application on the smartphone that is configured to respond to the notification to present one or more user interfaces (see, e.g., fig. 27) may send a notification to the testing system to notify the test operator that an acoustic load change has occurred, or send a notification to any other suitable device (e.g., a web server) that may use the information to notify the user or audiologist. As described above, in one example, the circuit determines whether there is a change in the acoustic load by: for example, it is determined whether there is a change in the frequency response of the acoustic receiver by comparing the measured acoustic pressure of the acoustic signal (e.g., with respect to the front volume, the back volume, and/or the output port) compared to a reference frequency response. In one example, the change in acoustic load is determined by using reference information corresponding to an expected Sound Pressure Level (SPL) at a frequency or range of frequencies of the acoustic signal at the output of the microphone. This may be done, for example, by using a microphone 1030. However, this may also be accomplished by using microphone 1026 and/or microphone 1028, as a change in condition in either the front or rear cavities may result in an undesired audible signal at the output port of the receiver.

The methods in fig. 15 and 16 may be performed at any suitable time and may depend on whether the method is performed by a hearing device using acoustic receivers or whether the method is performed while the hearing device is in a test unit (rather than in the ear of a user in the case of a hearing aid) or is being used by a user.

Determining whether there is a change in the acoustic load of the acoustic receiver will be described with reference to fig. 17 to 19. As described above, the memory 922 may store reference information (see also fig. 6). In this example, the data representing the expected transfer function is shown as expected SPL information, shown by the points along the reference SPL information 1700. As also noted, the reference information includes functions that may be stored rather than actual data from which data may be obtained. As used herein, the function or data itself is used as reference information. The function may be used to determine points along a frequency response curve, for example, an expected transfer function generated using a reference load representing no blocking or acoustic leakage. The entire transfer function need not be stored. A single point on the curve at a particular frequency may be used, or multiple points may be stored. Furthermore, the transfer function of the entire measurement can be calculated and the appropriate points on the transfer function can be compared to the stored data points. In one example, the initial frequency or reference frequency response is the frequency or frequency response of the receiver without occlusion (such as wax induced occlusion) or acoustic leakage and is shown as reference SPL information 1700. The information representing the other curves 1702 is transfer function information indicative of the frequency response in the front volume based on different resistive test loads at the output port of the acoustic receiver. In one example, the reference SPL information 1700 is determined for a given voltage or current setting of the acoustic receiver as part of the manufacturing process. However, any suitable reference information may be used. The converted acoustic signal is compared to this information to determine whether there is a change in the acoustic loading.

Detecting the receiver output pressure via the microphone 1026, which is a front cavity microphone, the microphone 1026 may have certain advantages because the microphone 1026 is protected from direct wax build-up that may occur, for example, in the ear canal of a user. As shown in fig. 17, the change in acoustic load is shown by different resistance curves 1702, and an increase in sound pressure above the reference SPL information 1700 (reference information) is detected by the microphone 1026. A "best detection area" 1704 is identified, although all other areas may be used.

In one implementation, circuitry such as processor 930 provides an inaudible test signal as an electrical signal to the acoustic receiver in the front volume of the acoustic receiver, and microphone 1026 is operable to monitor the pressure caused by the inaudible test signal. This may allow in-ear testing to be performed so that the user is not aware of the occlusion test during, for example, normal operation of the device. As described above, the microphone 1026 is positioned to sense the acoustic pressure in the front volume of the receiver. In another example, the resulting signal from the microphone may be at a frequency below the mechanical resonance of the acoustic receiver. The reference information in this example corresponds to the expected sound pressure of the acoustic signal at a frequency below the mechanical resonance of the receiver in case the output of the acoustic receiver is not blocked. In this way, microphone 1026 may detect changes in the undesired acoustic loading simply by measuring a sufficiently high pressure level in the front cavity. Also, given the higher sound pressure level, microphone 1026 has a lower sensitivity than microphone 1028 and microphone 1030.

FIG. 18 illustrates information similar to that shown in FIG. 17 except for the posterior volume or cavity. As described above, load change detection may be determined by comparing an expected transfer function to a measured transfer function without having to store and process the large amount of data described below. In this back volume example, the "best detection zone" is shown at 1804, but comparisons may be made in all zones where there is a measurable difference between the output levels.

It can be seen that the reference SPL information 1800 can be used as the following reference information: the sensed sound pressure measured by the microphone 1028 is compared to the reference information to determine whether or not an acoustic load is present at the output of the acoustic receiver and, if desired, also to determine the degree of acoustic load. Storing data indicative of the other resistance curves 1802 allows the system to determine the degree of obstruction or seal degradation. For all sensors, any resistance curve can be used as reference information, if desired. It should also be appreciated that any other suitable reference information may be used as desired. As shown, the determination of whether an acoustic load is present based on back volume sound pressure detection may be a function of whether the detected sound pressure is above or below the sound pressure at a reference frequency or set of frequencies of the reference SPL information 1800. It is assumed that the input signal to the receiver when the sensor is making measurements is the same as the input signal used to generate the curve. This may be achieved by programming the diagnostic electrical input signal described above to have the same parameters (voltage, frequency and phase) as the electrical input signal used to generate data corresponding to the acoustic response versus frequency for the various resistance levels. If the input signal is different at the time of measurement, the degree of resistance may be extrapolated using a transfer function curve corresponding to the input signal level or using curves from different input signal levels. The latter approach would require storing in the memory of the acoustic device a plurality of sets of acoustic responses versus frequency curves for a plurality of electrical input signals within a range of possible input signals. Thus, knowledge of the input signals of the receiver is used to determine which transfer function to use or to extrapolate the transfer functions corresponding to the different input signals.

In fig. 18, it can be seen that there is good detection capability at the

resonant frequencies

1808 and 1810. Furthermore, since the microphone 1028 is located furthest from the output port 1024 and behind the front cavity and the panel 1014 (see fig. 10), the risk of cerumen blockage is low for the microphone 1028. The sound pressure level in the back volume is also relatively high and therefore a lower sensitivity microphone 1028 may be desirable.

Fig. 19 similarly illustrates examples of reference information 1900 (reference SPL) and a resistance curve 1902 (data representing values of the resistance curve) that may be used by the described system to determine whether there is a change in acoustic loading associated with an acoustic receiver. These curves illustrate information associated with the output port of the acoustic receiver. Full occlusion detection can be accomplished by only pressure measurements similar to those of the anterior chamber. Also, for a given input signal to the receiver, the data associated with resistance curve 1902 may be used in conjunction with other sensors to detect varying degrees of occlusion. As described above, any sensor may be used alone to detect partial obstruction.

Referring back to fig. 10 and 22-27, the different positions of the various sensors are shown in fig. 10 using dashed lines. It will be appreciated that a practical sensor assembly may have a housing portion mounted to the outer surface of the receiver housing such that the sensor is not physically located in the front and rear volumes or output ports but is positioned to sense pressure in the respective positions as further shown in fig. 22-27. A port through the wall of the receiver housing may be used which allows the sensor to measure the sound pressure. Any other suitable configuration may also be employed. As shown, the microphone 1026 may also be suitably positioned to measure the pressure in the front volume in front of the linkage 1016. The microphone 1028 may be positioned along a rear sidewall in the rear volume, along a front (toward the output port 1024) sidewall behind a duct defining at least a portion of the output port, or at any suitable location. The microphone 1030 may be positioned to measure the sound pressure within the pipe at the output port. In this example, a microphone 1030 is shown placed to measure pressure behind the wax guard 1025 to minimize wax build up on the sensor. As also shown in some of fig. 22-28, the electroacoustic transducer is positioned to sense pressure in the front volume of the receiver and is disposed on a substrate, such as a flexible printed circuit board or other substrate forming (defining) at least a portion of the front volume of the receiver. Similarly, in other examples, the electroacoustic transducer is positioned to sense pressure in the back volume of the receiver and is disposed on a substrate forming part of the back volume of the receiver. Also in other examples, the electro-acoustic transducer is positioned to sense pressure in the receiver output and the electro-acoustic transducer is disposed on a substrate that forms part of the receiver output. Fig. 28 illustrates an example of sensor location in an acoustic receiver, where the sensor forms part of the receiver housing and defines part of the front volume. However, any suitable location may be used.

In one example, determining the change in the acoustic loading is not accompanied by any correction using the predistortion signal. However, it will be appreciated that the equalization correction may be requested to be applied to allow the user to have better performance, for example, in the case of partial congestion.

Fig. 20 illustrates an example of a user interface that may be presented on a display of an external test system that is testing a hearing device. The test system includes a display, a processor, memory, and associated interface circuitry for allowing communication with the hearing device and, if desired, other devices and networks. As shown, user interface 2600 presents data representing whether a change in acoustic load has been detected, which is shown generally as

information

2602, 2064, 2606, and 2608. For example, if the degree of change in the acoustic load indicates that cerumen blockage should be removed, such information can be provided to a test operator so that the acoustic receiver can be cleaned or repaired. More specific information about the occlusion position may also be provided, for example as shown by information 2604 indicating that an occlusion is detected and that the front volume of the acoustic receiver has been affected. This may result in the hearing device requiring different types of maintenance operations. As shown by information 2606, a type of change in acoustic loading may be identified. In this case, a seal leak can be identified in comparison to a blockage caused, for example, by cerumen. As shown by message 2608, a notification can be issued that the wax guard on the acoustic receiver should be changed. Other information may be provided in addition to or in place of the information indicated herein. For example, a level or degree of obstruction may be identified, e.g., "low or high level obstruction" indicating a determined amount of change depending on the acoustic load. For example, if there is a large acoustic load variation compared to the reference information, a high level of obstruction may occur. If a slight change in acoustic loading is detected, the amount of occlusion may be indicated as low. As described above, if there is a low level of obstruction, the user may still be allowed to use the device, but equalization corrections or other suitable corrections may be provided in an attempt to alleviate the low level of obstruction until such time as a higher level of obstruction is detected.

Fig. 21 illustrates another interface 2700 in which the degree of obstruction is indicated by presenting information 2702 to, for example, a user's smartphone or wearable device or test system. As indicated at block 2704, a user may be allowed to choose to implement a predistortion operation to overcome a detected occlusion level or a seal leak level. The user interface information shown in fig. 20 and 21 may be regarded as notification information.

As described above, one or more sensors may be used in conjunction with the front volume, back volume, or receiver output port (acoustic channel) to monitor changes in the characteristics of the acoustic receiver. In this way, an automatic detection of ear wax accumulation, acoustic leakage (e.g. sealing leakage of a seal around the acoustic receiver) is provided when the acoustic receiver is in place in the ear of a user. As described above, the characteristic change may be a change in the expected transfer metric in the form of a change in the frequency response to the receiver. For example, reference information such as data representing the transfer function of the receiver before any wax build-up is used to detect incremental changes in acoustic blockage corresponding to wax build-up in the hearing aid. Similarly, reference information corresponding to a transfer function before acoustic leakage of the receiver is used. The above techniques may also determine the severity or extent of the condition present. As described above, detecting changes in receiver conditions can be accompanied by equalization to automatically compensate for changes in conditions associated with the receivers, if desired, but this may be undesirable.

As mentioned above, the notification of the test result may also be pushed to other devices, such as wearable devices, smartphones or any other suitable device. In response to determining that there is a change in the acoustic load, in one example, the processor sends at least one of a wireless notification to the remote device indicating that a change in the acoustic load has been detected, or sends an electrical signal to the acoustic earpiece that causes the acoustic earpiece to produce an audible notification, or sends a notification signal to the hearing device that causes a visual or audible generator, such as an LED, speaker, vibration mechanism, or other component of the hearing device, to be activated. The reference information may be absolute or relative to a threshold of earlier measurements and the test results as described above may be transmitted as a pass/fail, numerical or complete frequency sweep indication. This information may be conveyed in the form of an estimate of the acoustic impedance of the occlusion, or raw data may be conveyed, for wax build-up levels deemed acceptable. The raw test data may be the frequency response of the receiver, resonance variations such as the frequency of peaks or valleys, quality factors, frequency variations, amplitude variations at a particular frequency or range of frequencies, curves showing multiple characteristics detected as transmitted. For example, initial frequency response information such as an initial frequency response of the device at the time of factory new or other operation point of the device may be stored as the reference information. Test information known in the art may be communicated using a suitable protocol, such as I2C, UART, SPI, GPIO, Soundwire, or other suitable wired or wireless communication protocol.

In addition, the resulting determination from the cerumen buildup test may be uploaded to a web server of the manufacturer or audiologist serving the device so that remote monitoring of the health of the unit may be performed. The web server receiving the data then evaluates the test results and if the test results exceed a threshold, the web server initiates an electronic calendar event to set an appointment for the user of the device and the audiologist or other service provider to get the device repaired. In this way, a push operation occurs such that an active maintenance operation can be performed before the device reaches an unacceptable performance operating level from the user's perspective.

In one example, a front volume sensor is used to monitor low frequency information. In this example, an inaudible test signal may be injected into the receiver such that the sound is below a user-detected threshold and used to monitor the performance of the acoustic receiver. In this way, unobtrusive techniques are used to determine changes in the characteristics of the receiver using the front volume sensor. When the device is in the user's ear or used by the user, the test can be done without the user knowing that the device is being tested. A longer measurement time may be required in view of the low sound pressure being detected, although the measurement time is still suitable for the application. If the device is for a hearing impaired individual of known impaired frequency, the test signal may be set to a frequency below the individual's detectable frequency rather than inaudible, if desired. The test signal may be set to an inaudible level for a particular user even if the user is not hearing impaired.

When the monitored information is transmitted to a different remote device, such as a wearable device or smartphone, the smartphone application may accumulate the results of the measurements, and if the results of the measurements reach an undesirable threshold, the smartphone application may send a text message or screen message to the user informing the user that the device should be serviced. The threshold determination may also be done by a processor in the hearing device, such that the hearing device sends a "failure" message informing the user of the device that the device needs service, as described above. When the measured information approaches a critical threshold, the remote device may also initiate a calendar event to provide advanced service of the device before the device reaches an undesirable threshold (where the user's hearing ability is affected) or when the performance of the device is below a desired level.

In addition, it has been found that the use of a back volume sensor may provide advantages such as, but not limited to, providing good detection capability at the resonant frequency of the receiver and a low likelihood of cerumen occlusion in the back volume, among others. In some cases, a front volume sensor may be desirable because it may provide a large operating range, less risk of wax blockage than the output port, and may detect changes in acoustic loading without using reference frequency response information, among other advantages. The use of an output port sensor may be desirable in some applications because of the good detection at resonant frequencies and the possibility of using pressure measurements to detect a complete occlusion, among other advantages. However, it will be appreciated that any suitable sensor or combination of sensors may be required, among other things, depending on a given application and desired operation.

While the present disclosure and what are considered presently to be the best modes thereof have been described in a manner that establishes possession thereof by the inventors and that enables those of ordinary skill in the art to make and use the same, it will be understood and appreciated that there are many equivalents to the exemplary embodiments disclosed herein and that myriad modifications and variations may be made thereto without departing from the scope and spirit of the disclosure, which are to be limited not by the exemplary embodiments but by the appended claims.

Claims

1. An acoustic device, comprising:

an armature-based acoustic receiver comprising a housing having a diaphragm coupled to the armature, the diaphragm defining a front volume and a back volume, the front volume coupled to an output of the housing;

at least one electro-acoustic transducer located in at least one of the front volume, the back volume, and the output of the receiver; and

a circuit operable to determine whether there is a change in the acoustic signal of the receiver based on the pressure sensed by the at least one electroacoustic transducer,

wherein the change in the acoustic signal is indicative of a change in an acoustic load coupled to the receiver,

wherein the circuitry is operable to determine whether there is a change in the acoustic signal by comparing data representing a measured delivery metric of the earpiece to data representing an expected delivery metric of the earpiece,

wherein the measured transfer metric is a ratio of an acoustic output signal of the receiver to an electrical input signal of the receiver, and the expected transfer metric is a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference test load.

2. The acoustic apparatus of claim 1, wherein the circuit is operable to compare the measured transfer metric to the expected transfer metric for a frequency range between about 1 octave below a resonant frequency of the receiver and about 1 octave above the resonant frequency of the receiver.

3. The acoustic apparatus of claim 1, wherein the circuit is operable to provide an inaudible test signal as the electrical input signal, and wherein the at least one electro-acoustic transducer is located in the front volume of the receiver.

4. The acoustic apparatus of claim 1, wherein the circuit is operable to provide a notification when there is a change in the acoustic signal indicative of a change in the acoustic load.

5. The acoustic apparatus of claim 1, wherein the apparatus comprises an acoustic load acoustically coupled to the output of the receiver.

6. The acoustic device in accordance with claim 4,

wherein the change in the acoustic signal is indicative of a change in occlusion of the output section, and

wherein the expected transfer metric is a ratio of the reference acoustic output signal to a reference electrical input signal for a reference test load representing non-blocked headphones.

7. The acoustic device in accordance with claim 4,

wherein the change in the acoustic signal is indicative of a change in acoustic leakage,

wherein the expected transfer metric is a ratio of the reference acoustic output signal to a reference electrical input signal for a reference test load comprising a reference leakage.

8. The acoustic device of claim 4, wherein the electroacoustic transducer is positioned to sense pressure in the front volume of the receiver and is disposed on a substrate forming part of the front volume of the receiver.

9. The acoustic device of claim 4, wherein the electroacoustic transducer is positioned to sense pressure in the back volume of the receiver and is disposed on a substrate forming part of the back volume of the receiver.

10. The acoustic device of claim 4, wherein the electroacoustic transducer is positioned to sense pressure in the output of the receiver and is disposed on a substrate forming part of the output of the receiver.

11. An armature-based acoustic receiver, comprising:

a housing having a diaphragm coupled to an armature, the diaphragm defining a front volume and a back volume, the front volume coupled to an output port of the housing; and

at least one electro-acoustic transducer positioned to sense pressure in at least one of the front volume and the back volume to determine whether there is a change in an acoustic signal of the receiver based on the sensed pressure, wherein the change in the acoustic signal is indicative of a change in an acoustic load coupled to the receiver,

wherein the data representing the measured delivery metric of the headphones is compared with the data representing the expected delivery metric of the headphones to determine whether there is a change in the acoustic signal,

12. An integrated circuit, the integrated circuit comprising:

circuitry operable to apply an electrical input signal at an output of the integrated circuit for an armature-based acoustic receiver;

circuitry operable to determine whether there is a change in the acoustic signal of the earpiece by comparing the measured transfer metric to an expected transfer metric,

the measured transfer metric is a ratio of an acoustic output signal of the receiver to the electrical input signal, and the expected transfer metric is a ratio of a reference acoustic output signal of the receiver to a reference electrical input signal of the receiver for a reference test load.

13. The integrated circuit of claim 12,

the circuitry is operable to determine whether there is a change in the acoustic signal by comparing data representing a measured delivery metric of the earpiece to data representing an expected delivery metric of the earpiece.

14. The integrated circuit of claim 13, wherein the circuit is operable to compare the measured transfer metric to the expected transfer metric for a frequency range between about 1 octave below a resonant frequency of the receiver and about 1 octave above the resonant frequency of the receiver.

15. The integrated circuit of claim 13, wherein the circuit is operable to provide an inaudible test signal as the electrical input signal, and wherein at least one electroacoustic transducer is located in a front volume of the receiver.

16. The integrated circuit of claim 13, wherein the circuit is operable to provide a notification when there is a change in the acoustic signal indicative of a change in acoustic loading.

17. The integrated circuit of claim 13, wherein the integrated circuit,

wherein the change in the acoustic signal is indicative of a change in occlusion of the output, an

18. The integrated circuit of claim 13, wherein the integrated circuit,